Assessing Incidence of and Risk Predictors Ascertained at Diagnosis for Symptomatic Venous Thrombotic Events in Pediatric Cancer Patients: A 20-Year Population Based Study from the Maritimes, Canada
Bibliographic record
Abstract
Abstract Background: Symptomatic venous thrombotic events (sVTE) are a well-recognized complication in pediatric cancer patients. Accurate data on true incidence of sVTE is limited due to large variability in design and methodology of previously published reports. As well, risk factors are unclear. Moreover, the limitations of several of the previously described risk factors for sVTE include (i) limited generalizability to all pediatric cancers, (ii) hemostatic protein lab values are altered by cancer itself, (iii) long turn-around times from laboratories and (iv) testing restricted to specialized labs. There is a need to identify risk factors for sVTE in pediatric cancer patients that are easily evaluated at the time of cancer diagnosis. Aims: Establish incidence of sVTE and identify risk factors associated with sVTE in pediatric cancer patients. Methods: All pediatric cancer patients in the 3 Maritime Provinces of Nova Scotia, New Brunswick and Prince Edward Island are treated at IWK Health Center (IWK) in a shared care model. This provides a population-based cohort of pediatric cancer patients from the Maritimes. After ethics approval, all pediatric cancer patients treated at the IWK from 1995 to 2014 with sVTE were identified through a conceptual framework as follows. Clinical (including sVTE) and laboratory data was extracted from the: (i) Pediatric oncology hospital database (ii) Provincial Cancer in Young People registry (iii) Electronic medical records (iv) Pharmacy database (v) IWK Central Venous Access Database and (vi) Hospital health records. After extraction, data from all sources was amalgamated and cross-verified. SPSS version 21 was used for statistical analysis. Central veins were defined as veins including and proximal to the axillary vein in the upper extremity and femoral vein in the lower extremity. sVTE was defined as radiologically documented VTE with at least one sign/symptom directly associated with VTE. Patients with VTE during relapsed disease and those with asymptomatic/incidentally diagnosed VTE were excluded from analysis. Results: Forty-seven (4.356±0.01%) of the 1079 patients had sVTE. The mean age at diagnosis for sVTE patients was 10.142 years. The mean age at diagnosis of the remaining patients (n=1032) was 7.451 years. The difference in the mean ages in the 2 categories was statistically significant (p=0.001). The gender ratio was M:F: 1.765:1 in patients with sVTE as compared to M:F: 1.123:1 in the remainder of the patients (p=0.336). Central veins were the most common location for sVTE (72.3%, n=34). Other less common locations included 1 each of sinovenous, mesenteric, cardiac, renal vein thrombosis and pulmonary embolism. On univariate analysis for risk factors, age > 10 years at diagnosis (P = 0.021), type of cancer (P = 0.028) and non-O blood group (P = 0.043) were associated with sVTE, while gender (p=0.336) and use of asparaginase (p=0.663) were not. On multivariate analysis, age > 10 years at diagnosis (odds ratio [OR]: 1.737 [1.066-2.831], p=0.027), and type of cancer (non-brain tumor; OR: 11.154 [1.527-81.451], P=0.017) were associated with sVTE. The association of non-O blood group with sVTE trended towards significance (OR: 1.886 [0.962-3.695], p=0.065) likely due to small numbers and difficulty identifying sVTE retrospectively. Conclusion: In a large population-based cohort of patients, we established incidence of sVTE in pediatric cancer patients. The study identified that sVTE occur in central veins in almost 3/4th of the patients. As well, we evaluated easily available and independent risk factors for sVTE in pediatric cancer patients. Further larger prospective and multicenter studies are needed to validate these observations and develop a risk prediction model for sVTE in pediatric cancer patients. Disclosures No relevant conflicts of interest to declare.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".